1.5k citations · 2k across the 57 of their papers we have counts for
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SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs
Jie Sun, Yu Liu, Lu Han +9
While transformer-based Large Language Models (LLMs) theoretically support massive context windows, they suffer from severe performance degradation when processing long numerical s…
Confidence Before Answering: A Paradigm Shift for Efficient LLM Uncertainty Estimation
Changcheng Li, Jiancan Wu, Hengheng Zhang +5
Reliable deployment of large language models (LLMs) requires accurate uncertainty estimation. Existing methods are predominantly answer-first, producing confidence only after gener…
bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs
Wence Ji, Jiancan Wu, Aiying Li +5
With the rapid advancement of large language models (LLMs), their robustness against adversarial manipulations, particularly jailbreak backdoor attacks, has become critically impor…
Enhancing Temporal Sensitivity of Large Language Model for Recommendation with Counterfactual Tuning
Yutian Liu, Zhengyi Yang, Jiancan Wu +1
Recent advances have applied large language models (LLMs) to sequential recommendation, leveraging their pre-training knowledge and reasoning capabilities to provide more personali…
Robust Preference Optimization via Dynamic Target Margins
Jie Sun, Junkang Wu, Jiancan Wu +5
The alignment of Large Language Models (LLMs) is crucial for ensuring their safety and reliability in practical applications. Direct Preference Optimization (DPO) has emerged as an…
MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
Chengpeng Li, Zheng Yuan, Hongyi Yuan +6
In math reasoning with large language models (LLMs), fine-tuning data augmentation by query evolution and diverse reasoning paths is empirically verified effective, profoundly narr…